A field of seismology focuses on the use of acoustic waves to prospect for hydrocarbon sandstones, carbonates, and shale reservoirs. Exploration seismology provides information that, when integrated with other geological information, can provide an understanding of the structure and distribution of types of subsurface materials. For example, most oil companies rely on seismic interpretation to select sites for drilling exploratory oil wells or to develop known sites.
Although seismic data is used to map geological structures rather than to find petroleum directly, the gathering of seismic data has become a vital part of the process of selecting sites for further exploration and drilling. Experience has shown that the use of seismic data greatly improves the accuracy of structural and stratigraphic maps and reduces the risks of uncertainty when drilling new prospects.
In order to search for hydrocarbon accumulations in the earth, geoscientists are using methods of remote sensing to look below the earth's surface. A routinely used technique is the seismic reflection method where man-made sound waves are generated near the surface. The sound propagates into the earth, and whenever the sound passes from one rock layer into another, a small portion of the sound is reflected back to the surface where it is recorded. Typically, hundreds to thousands of recording instruments are employed. Sound waves are sequentially excited at many different locations. From all these recordings, a two- or three-dimensional image of the subsurface can be obtained after significant data processing.
Measurements derived from these data are called seismic attributes. The most commonly used attribute is amplitude of the recorded sound waves because it allows identification and interpretation of many subsurface features such as the boundaries between different rock layers. Many other properties of the subsurface, however, are not sufficiently identifiable on images of basic seismic amplitude.
Several types of seismic attributes are useful, such as those disclosed in “Complex Seismic Trace Analysis” by Tanner, Koehler, and Sheriff 1979, Geophysics, vol. 44, no. 6, pp. 1041-1063”, incorporated herein by reference in its entirety. The instantaneous phase attribute, for example, is generally insensitive to amplitude and measures the continuity of seismic events. It can be used to show subtle non-conformities where subsurface layers are truncated by an erosion surface. Further, an apparent polarity attribute has been used to discern between gas and water reservoirs. A reflection strength attribute has been used to discern between chalk (high amplitude) and sands/shales (low amplitude). Such attributes are known as complex trace attributes and are derived by using the Hilbert transform.
The seismic trace amplitude, herein referred to by the capital letter, A, is treated as the real part of the (complex) analytical signal while the imaginary part of the signal, herein referred to by the capital letter, Q, is computed by taking the Hilbert transform of the amplitude, A. An envelope is computed by taking the square root of the sum of the squares of the real and imaginary components, A and Q, whereas the phase, herein referred to by the capital letter, I, is computed by taking the inverse tangent of the imaginary and real components. Finally, the frequency is computed as the rate of change of the phase, I.
These computations may be carried out at each sample of the seismic trace. Three principal attributes—envelope, phase and frequency—have been established in the field of seismic interpretation:
1) Instantaneous envelope (reflection strength), which is sensitive to changes in acoustic impedance and thus to lithology, porosity, hydrocarbons, and thin-bed tuning;
2) Instantaneous phase, which is useful for tracking reflector continuity and, therefore, for detecting unconformities, faults and lateral changes in stratigraphy; and
3) Instantaneous frequency, which is useful in identifying abnormal attenuation and thin-bed tuning.
However, these principle attributes are deficient to show many of the internal features of a subsurface structure. What is needed are methods for computing other attributes of seismic data that will enhance an ability to discern features of subsurface structures.